• Lots of manual steps
• Hard to reproduce
• Mistakes are easily made and hard to track
• The steps aren’t recorded
• Using multiple independent tools
• How do we keep track of which file versions people have?

• It is easily repeatable
• It is easily extendable
• It is automated
• It minimises mistakes
• It is fast
• It builds trust

Image taken from: The Turing Way book

• Easy for others to use
• Others can change and adapt
• All steps are recorded
  • Including whilst it is built
• Automated and fast
• Open and promotes trust

Image taken from: The Turing Way book

No, it is a building block that’s essential for data science!

• Open-source tools
• Version control with git
• To consider reproducibility
• Time to learn

Open source tools are:

• Used by millions - huge supportive online community
• Flexible to all data sources
• Free for anyone to use - it is easier to share
• Flexible to all output types

Image taken from: The Turing Way book

Tracking the three Ws: Who made Which change and Why?

• One place to store your code
• You and collaborators are free to write and develop locally
• Complete documented history of all changes made
• Easy to share
• Your future self will thank you!

We want to look back and be able to repeat our work easily and quickly.

What are the benefits?

• Helps build trust
• Not reliant on single individual
• Can be adapted and re-used

Image taken from: The Turing Way book

Before we start, here are a few things to consider:

• IT infrastructure available
• Data privacy - where and how am I storing my data?
• Expertise - what training do I need?
• Legacy systems - what are the barriers to transitioning?

Image taken from: The Turing Way book

The building blocks of a RAP:

• Version control
• Using open-source tools
• Create reproducible code

… are useful in their own right, each will improve the auditability, speed and quality of your work.

RAP has been successfully rolled out in 10s of projects across the UK government.

It is now part of the best practice documentation.

Work continues across the government to roll out RAP to more projects.

govdown - R package to recreate our UK government website template.

drake - R package to streamline reproducible pipelines in R.

snapcraft - python package to solve those dependency issues!

We aim to raise the aid community’s capacity for using Data Science to meet the Sustainable Development Goals.

We’ll link up Data Scientist mentors from the campus with mentees. Together we’ll set plan out a project, describing:

• What the project is, its impact and scope
• The resources, expertise and time will we’ll need
• And, how we’ll work together during the project

As we plan out our project, we’ll be considering those sometimes difficult aspects of RAP:

• IT infrastructure available
• Data privacy - where and how am I storing my data?
• Expertise - what training do I need?
• Legacy systems - what are the barriers to transitioning?

• The UK goverment RAP website.

• A free RAP course to teach you all you need to know.

• How the Data Science Campus sets its coding standards.

• A new open-source book from the Alan Turing insititute setting out how to do reproducible data science.

• The github page for this presentation and other materials is here.

• Get involved in the UK government RAP champion network here.

Many of the beautiful images used in this presentation were taken from The Turing Way book.

Full citation:

The Turing Way Community, Becky Arnold, Louise Bowler, Sarah Gibson, Patricia Herterich, Rosie Higman, … Kirstie Whitaker. (2019, March 25). The Turing Way: A Handbook for Reproducible Data Science (Version v0.0.4). Zenodo. http://doi.org/10.5281/zenodo.3233986